ai-observability
Use when adding Spring AI-specific model observations, token usage, latency, externally configured cost attribution, advisor…
Use when building batch jobs, ETL pipelines, scheduled imports/exports, or any chunk-oriented bulk processing with Spring Batch. Covers the Spring Batch 5 / Boot 3 builder API, restartability and idempotent job parameters, reader/writer thread-safety, fault tolerance, and chunk
Claude Code
$ npx -y skills add rrezartprebreza/spring-boot-skills --skill spring-batch --agent claude-code
Codex
$ npx skills add rrezartprebreza/spring-boot-skills --skill spring-batch -a codex -y
Cursor
$ npx skills add rrezartprebreza/spring-boot-skills --skill spring-batch -a cursor -y
Gemini CLI
$ npx skills add rrezartprebreza/spring-boot-skills --skill spring-batch -a gemini-cli -y
GitHub Copilot
$ npx skills add rrezartprebreza/spring-boot-skills --skill spring-batch -a github-copilot -y
OpenCode
$ npx skills add rrezartprebreza/spring-boot-skills --skill spring-batch -a opencode -y
Windsurf
$ npx skills add rrezartprebreza/spring-boot-skills --skill spring-batch -a windsurf -y
name: spring-batch description: > Use when building batch jobs, ETL pipelines, scheduled imports/exports, or any chunk-oriented bulk processing with Spring Batch. Covers the Spring Batch 5 / Boot 3 builder API, restartability and idempotent job parameters, reader/writer thread-safety, fault tolerance, and chunk transaction boundaries.
Spring Boot 3.x ships **Spring Batch 5**. The API changed significantly from 4.x — most online examples are wrong. The two rules that break the most agent-generated code:
1. **Do NOT add `@EnableBatchProcessing`.** Boot auto-configures the `JobRepository`, `JobLauncher`, and transaction manager. Adding `@EnableBatchProcessing` **disables** that auto-configuration and you lose all the wired beans. 2. **`JobBuilderFactory` and `StepBuilderFactory` are gone.** Build jobs and steps with `new JobBuilder(name, jobRepository)` / `new StepBuilder(name, jobRepository)`, injecting the `JobRepository` and `PlatformTransactionManager` Boot already created.
@Configuration
@RequiredArgsConstructor
public class OrderExportJobConfig {
@Bean
public Job orderExportJob(JobRepository jobRepository, Step exportStep) {
return new JobBuilder("orderExportJob", jobRepository)
.incrementer(new RunIdIncrementer()) // lets the same job be re-run; see "Idempotency"
.start(exportStep)
.build();
}
@Bean
public Step exportStep(JobRepository jobRepository,
PlatformTransactionManager txManager, // Boot's, injected — do NOT new one up
ItemReader<Order> reader,
ItemProcessor<Order, OrderRow> processor,
ItemWriter<OrderRow> writer) {
return new StepBuilder("exportStep", jobRepository)
.<Order, OrderRow>chunk(500, txManager) // chunk size is the commit interval — and a TX boundary
.reader(reader)
.processor(processor)
.writer(writer)
.faultTolerant()
.skip(FlatFileParseException.class)
.skipLimit(50)
.build();
}
}`chunk(500, txManager)` means: read 500 items, process each, hand the list of 500 to the writer, **commit one transaction**, repeat. The chunk is the unit of restart and the unit of rollback.
A `JobInstance` is identified by its **identifying** `JobParameters`. Launch the same job with the same identifying parameters twice and you get:
JobInstanceAlreadyCompleteException: A job instance already exists and is complete
This is by design — Batch refuses to re-run completed work. Two ways to handle it:
// Option A — RunIdIncrementer on the job (above) + JobLauncherApplicationRunner bumps run.id each launch.
// Option B — add a unique identifying parameter yourself when launching:
JobParameters params = new JobParametersBuilder()
.addString("status", "COMPLETED") // identifying — part of the instance key
.addLong("run.id", System.currentTimeMillis()) // identifying & unique — makes each run a new instance
.toJobParameters();Mark a parameter **non-identifying** with the `false` flag when it's metadata that shouldn't change the instance identity (e.g. a request id you log but don't key on):
.addString("requestId", requestId, false) // non-identifying — excluded from the instance keyA **failed** job, by contrast, is *resumed* when relaunched with the **same** parameters — it skips completed steps and restarts the failed step from the last committed chunk. That is the point of the metadata tables. Don't defeat it by always passing a unique parameter if you want resume-on-failure.
@Bean
@StepScope // required: late-binds jobParameters at step execution, not context startup
public JpaPagingItemReader<Order> orderReader(
EntityManagerFactory emf,
@Value("#{jobParameters['status']}") String status) {
return new JpaPagingItemReaderBuilder<Order>()
.name("orderReader")
.entityManagerFactory(emf)
.queryString("SELECT o FROM Order o WHERE o.status = :status ORDER BY o.id") // ORDER BY is MANDATORY
.parameterValues(Map.of("status", OrderStatus.valueOf(status)))
.pageSize(500) // keep pageSize == chunk size
.build();
}rows in arbitrary order across pages → rows get **skipped or processed twice**. This is silent data corruption, not an error.
safe for multi-threaded steps. For a non-thread-safe reader in a multi-threaded step, wrap it in `SynchronizedItemStreamReader`.
`PENDING` to `DONE` while the reader pages `WHERE status = 'PENDING' ORDER BY id`, the result set shifts under you and pages are missed. Read into a stable snapshot, page by immutable `id`, or use a cursor reader.
@Component
public class OrderProcessor implements ItemProcessor<Order, OrderRow> {
@Override
public OrderRow process(Order order) {
if (order.getTotal().isZero()) {
return null; // Note: null = FILTER this item; it is NOT written and NOT an error
}
return OrderRow.from(order);
}
}Returning `null` silently drops the item from the chunk. That's a feature (filtering) but a footgun if you returned `null` by accident expecting it to pass through.
In 5.x the writer receives a `Chunk<? extends T>`, **not** `List<? extends T>`:
@Override public void
Production-grade Claude Code and Codex skills for Spring Boot developers
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